code: def conv_params(fsize, nfm, strides=1, relu=True, batch_norm=True):
      return dict(
          fshape=(fsize, fsize, nfm),
          strides=strides,
          activation=(Rectlin() if relu else None),
          padding=(fsize // 2),
          batch_norm=batch_norm,
          init=Kaiming(local=True),
      )
  
file_path: neon/examples/imagenet/network_msra.py
imports: from builtins import zip
  import itertools
  from neon.initializers import Kaiming
  from neon.layers import Conv, Pooling, GeneralizedCost, Activation
  from neon.layers import MergeSum, SkipNode
  from neon.transforms import Rectlin, Softmax, CrossEntropyMulti
  from neon.models import Model
label_desc: Use image node_id 1 for calling a global function with example usage: conv_params(fsize, nfm, strides, relu, batch_norm) and returns: dict